Using existing NHS datasets to determine outcomes of cancer medicines: a feasibility study

Kelly Baillie; Tanja Mueller; Jiafeng Pan; Christine Crearie; Jennifer Laskey; Robert Jones; Marion Bennie

Using existing NHS datasets to determine outcomes of cancer medicines: a feasibility study

Kelly Baillie, Tanja Mueller, Jiafeng Pan, Christine Crearie, Jennifer Laskey, Robert Jones, Marion Bennie

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Abstract

Based on recent clinical trial evidence, updated treatment guidelines in the UK recommend high-intensity statin therapy (atorvastatin 80mg) for secondary prevention of cardiovascular disease. However, with this high statin dose, there are concerns about a potential increase in the incidence of statin-related side effects, which might affect patients’ adherence and, in turn, clinical outcomes. Hence, this study aimed to evaluate the effect of statin intensity on adherence and persistence to therapy.

Original language	English
Number of pages	2
Publication status	Accepted/In press - 18 Jun 2018
Event	34th International Conference on Pharmacoepidemiology and Therapeutic Risk Management - The Prague Congress Centre, Prague, Czech Republic Duration: 22 Aug 2018 → 26 Aug 2018

Conference

Conference	34th International Conference on Pharmacoepidemiology and Therapeutic Risk Management
Country/Territory	Czech Republic
City	Prague
Period	22/08/18 → 26/08/18

Keywords

cancer medicines
medicine results

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Baillie-etal-ICPTRM-2018-Using-existing-NHS-datasets-to-determine-outcomes-of-cancer-medicinesAccepted author manuscript, 510 KB

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title = "Using existing NHS datasets to determine outcomes of cancer medicines: a feasibility study",

abstract = "Based on recent clinical trial evidence, updated treatment guidelines in the UK recommend high-intensity statin therapy (atorvastatin 80mg) for secondary prevention of cardiovascular disease. However, with this high statin dose, there are concerns about a potential increase in the incidence of statin-related side effects, which might affect patients{\textquoteright} adherence and, in turn, clinical outcomes. Hence, this study aimed to evaluate the effect of statin intensity on adherence and persistence to therapy.",

keywords = "cancer medicines, medicine results",

author = "Kelly Baillie and Tanja Mueller and Jiafeng Pan and Christine Crearie and Jennifer Laskey and Robert Jones and Marion Bennie",

year = "2018",

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note = "34th International Conference on Pharmacoepidemiology and Therapeutic Risk Management ; Conference date: 22-08-2018 Through 26-08-2018",

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TY - CONF

T1 - Using existing NHS datasets to determine outcomes of cancer medicines

T2 - 34th International Conference on Pharmacoepidemiology and Therapeutic Risk Management

AU - Baillie, Kelly

AU - Mueller, Tanja

AU - Pan, Jiafeng

AU - Crearie, Christine

AU - Laskey, Jennifer

AU - Jones, Robert

AU - Bennie, Marion

PY - 2018/6/18

Y1 - 2018/6/18

N2 - Based on recent clinical trial evidence, updated treatment guidelines in the UK recommend high-intensity statin therapy (atorvastatin 80mg) for secondary prevention of cardiovascular disease. However, with this high statin dose, there are concerns about a potential increase in the incidence of statin-related side effects, which might affect patients’ adherence and, in turn, clinical outcomes. Hence, this study aimed to evaluate the effect of statin intensity on adherence and persistence to therapy.

AB - Based on recent clinical trial evidence, updated treatment guidelines in the UK recommend high-intensity statin therapy (atorvastatin 80mg) for secondary prevention of cardiovascular disease. However, with this high statin dose, there are concerns about a potential increase in the incidence of statin-related side effects, which might affect patients’ adherence and, in turn, clinical outcomes. Hence, this study aimed to evaluate the effect of statin intensity on adherence and persistence to therapy.

KW - cancer medicines

KW - medicine results

UR - https://www.pharmacoepi.org/meetings/34icpe/

M3 - Poster

Y2 - 22 August 2018 through 26 August 2018

ER -

Using existing NHS datasets to determine outcomes of cancer medicines: a feasibility study

Abstract

Conference

Keywords

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